Lake Ice in Canada: Improving one-dimensional lake ice modelling and investigating changing ice cover and trends
Notice bibliographique
Résumé
Lakes are a dominant geographic feature in northern landscapes, and lake ice demonstrates a strong relationship with air temperature and large-scale atmospheric patterns, showing that lake ice is sensitive to climate variability and change. Changes to present-day lake ice regimes could result in major ecosystem changes and lead to substantial economic and environmental changes. The Canadian Lake Ice Model (CLIMo) was selected to study lake ice in Canada. The first study objective identified that regionally specific measurements of snow and ice albedo can be used to improve the accuracy of lake ice simulations, where field measurements of snow and ice albedo for two temperate region lakes were used to improve CLIMo. The simulated results presented an improvement to ice-off timing to within 0 to 7 days of observations. The second study objective examined the radiation balance of a High Arctic Lake during the open water period and found that CLIMo was able to simulate the radiation balance during this period (Index of Agreement of 0.74 for net radiation). This information was used to simulate future open water conditions using the Arctic CORDEX CMIP5 RCP 8.5 conditions. Future open water duration is expected to increase by 12 to 14 days per decade with both net radiation and net shortwave radiation decreasing and net longwave radiation increasing. Using the model derived in the first study, an exploration of lake size and its representation in CLIMo was assessed to determine if we could create an adjustment factor that could adjust many lakes at once (a batch adjustment) based on a specified range of lake sizes. It was determined based on lake size and simulated ice-off, that no batch adjustment factor could be derived. However, individual adjustments can be done using the mean absolute error to determine length and mean bias error to determine direction. Finally, lake ice phonology and snow trends were assessed and changepoints in the lake ice phenology and snow trends were examined, to determine the overall magnitude and direction of trends and changepoint years across Canada. The trends and changepoints show that ice cover duration is decreasing, through earlier ice-off and later ice-on, and snow cover across Canada is showing decreasing snow depth, snow density and snow water equivalent. The results show that there is regional variability which means that lake ice phenology and snow are not changing the same everywhere across Canada. The observed regional variability in lake ice phenology and snow across Canada underscores the need to understand these changing patterns under a changing climate so that we can better understand and predict how lake ice phenology and snow will change in the future.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».